"Querying Elasticsearch (ES)" matching MCP servers:

Provides comprehensive tools for managing Elasticsearch clusters, including security management, search operations, and index administration. It enables users to monitor cluster health, handle InfoSec tasks, and execute complex queries using Elasticsearch Query DSL and ES|QL.

Transforms Elasticsearch into an AI-powered observability engine for analyzing logs, APM traces, and system metrics through natural language.

An MCP server that downloads Elasticsearch logs from Elastic Cloud via the Admin API.

Read-only MCP server that converts Elasticsearch logs into citable evidence for AI agents, offering deterministic log summarization and search tools.

Enables Claude Desktop to connect directly to Elasticsearch clusters for intelligent log analysis through natural language queries. Users can ask questions about their logs in plain English and get actionable insights without writing complex Elasticsearch queries.

MCP server for Kibana / Elasticsearch — log search, aggregations, index discovery, and dashboard browsing. Hits Elasticsearch REST API directly for log queries; falls back to Kibana Console proxy when no direct ES URL is configured. Supports ApiKey auth (best for agents), Basic auth, and anonymous access. All 5 tools are read-only (readOnlyHint: true). Returns structured JSON (outputSchema).

Enables LLM agents to search and analyze Elasticsearch logs for errors, detect recurring patterns, analyze error-rate trends, and retrieve full trace context through MCP tools.

Enables AI assistants to search Elasticsearch logs, retrieve log details, analyze service health, scan local codebases for APIs, and create Kibana dashboards.

A read-only MCP server that gives AI assistants natural language access to Elasticsearch/Kibana logs for querying and analysis.

Small production-oriented MCP server for diagnosing incidents from Elasticsearch logs with unknown schema. It provides tools for log discovery, retrieval, and issue diagnosis.

An MCP server that enables interaction with Elasticsearch and OpenSearch clusters for searching documents and managing indices. It provides tools for cluster health monitoring, index configuration, and general API requests.

Enables AI assistants to interact with Kibana dashboards, visualizations, and Elasticsearch data through read-only resources and executable tools for searching logs, exporting dashboards, and querying data.

Enables querying Amazon EKS cluster metrics from the Kubernetes API server, with filtering by metric name and labels, supporting both exact and regex patterns.

Enables comprehensive interaction with Elasticsearch APIs through natural language queries, specifically optimized for security analysis, threat detection, incident investigation, and compliance monitoring with advanced machine learning capabilities for anomaly detection.

A read-only MCP server exposing SLURM, GPFS, Prometheus (node exporter + DCGM GPU metrics) and generic Elasticsearch exploration as diagnostic tools for LLM-based HPC support assistants.

MCP server for querying observability data from Elasticsearch, SkyWalking, and Prometheus/VictoriaMetrics, enabling AI models to search logs, traces, and metrics across environments.

Enables AI to automatically diagnose bugs by querying logs, tracing call chains, and analyzing code across multiple log platforms like Elasticsearch and Loki.

Enables MCP-compatible AI clients to search and retrieve Elasticsearch application logs through a provided search tool.

Enables querying and managing Sentry projects, issues, and events through natural language.

Enables Cursor and Claude Code to inspect Kibana APM data—services, transaction and error groups, trace samples, and trace waterfalls—through Kibana's internal APM APIs. It focuses on Kibana-computed aggregates rather than raw logs or Elasticsearch documents.